179 citations · 329 across the 13 of their papers we have counts for
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cs.LG2022
Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs
Silvia Beddar-Wiesing, Giuseppe Alessio D'Inverno, Caterina Graziani +4
Graph Neural Networks (GNNs) are a large class of relational models for graph processing. Recent theoretical studies on the expressive power of GNNs have focused on two issues. On…
q-bio.QM2022★ 1 cited
Modular multi-source prediction of drug side-effects with DruGNN
Pietro Bongini, Franco Scarselli, Monica Bianchini +3
Drug Side-Effects (DSEs) have a high impact on public health, care system costs, and drug discovery processes. Predicting the probability of side-effects, before their occurrence,…